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sc-SPLASH extends the SPLASH statistical framework to barcoded scRNA-seq (10x Chromium) and spatial transcriptomics (10x Visium), enabling reference-free, statistics-first discovery of transcriptomic variation without a reference genome. Its standalone BKC preprocessing submodule is ~50× faster than UMI-tools, and the pipeline has demonstrated discovery of novel secreted proteins in non-model organisms, tumor-associated mutations, and spatially-regulated alternative splicing. Published in Nature Biotechnology (April 2026).

The LTS4 Laboratory at EPFL is recruiting a postdoc within the SATURNA multi-partner research initiative, focused on decoding RNA dynamics and disease mechanisms through AI innovation combined with context-aware biology. The role involves developing high-quality research programs, mentoring junior researchers, and collaborating with SATURNA industry and academic partners. A PhD in computational biology, AI, computer science, electrical engineering, physics, or applied mathematics is required; start date is Fall 2026.

Two postdoctoral positions in Prof. Charlotte Bunne's Artificial Intelligence in Molecular Medicine (AIMM) Lab at EPFL, spanning the School of Computer and Communication Sciences, School of Life Sciences, and EPFL AI Center. The research agenda covers biological foundation model architecture development—novel pretraining objectives, tokenisation, scalable architectures—multimodal learning across diverse biological data types, and agentic interfaces for drug discovery. PhD in machine learning, computer science, or computational biology plus large-scale AI development experience and a solid biological background are required; start Fall 2026.

A three-day hackathon at the Max Delbrück Center (MDC), Campus Berlin-Buch, Germany on September 2–4, 2026, jointly organized by scverse, CytoData Society, and EU-OPENSCREEN. The event advances image-based morphological profiling and single-cell perturbation analysis across three workstreams: image-based profiling with scverse tooling, single-cell perturbation tools for phenomics, and scalable model training with scverse data standards. Application notifications were issued June 8, 2026.

The 75th ASMS Annual Conference on Mass Spectrometry and Allied Topics is scheduled for June 6–10, 2027 at the George R. Brown Convention Center in Houston, TX. This premier annual meeting covers the full breadth of mass spectrometry including proteomics, metabolomics, lipidomics, imaging, and instrumentation. Registration and abstract submission details will be published by ASMS closer to the event date.

The twelfth annual CSHL meeting on CRISPR systems, fostering interactions between researchers applying CRISPR genome engineering and scientists studying fundamental CRISPR-Cas biology and bacterial defense mechanisms. Held August 11–15, 2026 at Cold Spring Harbor Laboratory, NY. Abstract submission deadline is June 8, 2026; late registration deadline is August 6, 2026.

10x Genomics is building a clinical diagnostics division and seeks a senior computational scientist to translate single-cell and spatial transcriptomics into clinically actionable biomarkers and diagnostics. The role requires implementing and optimizing ML and statistical algorithms on some of the largest single-cell biomedical datasets, developing scalable bioinformatics pipelines, and distilling complex biological findings into clinical insights. Requires a PhD in bioinformatics or computational biology with a minimum of 5 years of post-PhD industry experience and deep expertise in single-cell NGS.

A Keystone Symposia conference at Keystone Resort, CO (January 25–28, 2027) covering delivery strategies for nucleic acid therapeutics including RNA, DNA, and gene editing payloads across multiple tissue targets. Jointly held with J7 (Precision Genome Engineering). Registration and abstract submission opens July 2026.

Cardinal is a mass spectrometry imaging toolbox for R providing efficient preprocessing, spatial segmentation, and statistical classification of imaging MS datasets. It serves workflows in proteomics, lipidomics, and spatial metabolomics research. Released in Bioconductor 3.23 (v3.14.0).

FRASER (Find Rare Aberrant Splicing Events in RNA-seq) detects rare aberrant splicing events in transcriptome data using an autoencoder to model read-count expectations and a beta-binomial distribution to score outliers. It supports alternative splicing and intron-retention detection and is optimised for rare disease diagnosis pipelines. Released in Bioconductor 3.23 (v2.8.0).

AlphaDIA is an open-source, feature-free DIA (data-independent acquisition) proteomics search engine that performs machine learning directly on raw mass spectrometry signals, achieving end-to-end transfer learning across instruments without requiring spectral library features. Benchmarked at >120,000 precursors per run, it matches or exceeds other leading search engines. Published in Nature Biotechnology (2025); part of the AlphaX proteomics ecosystem from the Mann Lab.

Postdoctoral position in the CHI Lab supervised by Prof. David Clifton (Chair of Clinical Machine Learning, Oxford) to develop machine learning approaches for large-scale clinical datasets including physiological time-series, blood tests, medications, and diagnoses. The role involves creating analytical protocols, publishing peer-reviewed articles, and leading team members. Requires a PhD in AI, signal processing, or related field with strong Python/MATLAB programming and a solid publication record.

Three-year fixed-term research assistant position at the Human Technopole (Milan) to develop and optimize advanced proteomics workflows including single-cell, spatial, plasma, and clinical proteomics using mass spectrometry platforms. The role requires a PhD in biology/chemistry/biochemistry and at least 5 years of bottom-up proteomics experience, with proficiency in tools such as MaxQuant, DIA-NN, FragPipe, and Spectronaut. Background in machine learning applied to proteomics data analysis is valued.

Postdoctoral position in Prof. Matthias Mann's Department of Proteomics and Signal Transduction in Munich, focused on integrative analysis of large-scale proteomics, lipidomics, glycomics, and clinical datasets for Parkinson's disease research within an international consortium. The role involves developing machine learning methods for biomarker discovery and patient stratification, and building reproducible bioinformatics pipelines. Requires a PhD in bioinformatics, computational biology, or biostatistics and proficiency in Python.

Senior scientist role at 10x Genomics (Pleasanton, CA) to translate leading single-cell and spatial transcriptomics assay technologies into clinical diagnostics applications. Responsibilities include implementing computational and statistical methods on large-scale single-cell/spatial datasets, designing and validating biomarkers, and building reproducible bioinformatics pipelines across hundreds to thousands of samples. Requires a PhD in bioinformatics or computational biology plus a minimum of 5 years of post-PhD industry experience.

pertpy is a newly promoted scverse core package dedicated to single-cell perturbation experiment analysis, including CRISPR screens and compound treatments. It provides differential perturbation analysis, signature scoring, and dose-response modeling with purpose-built metadata handling and visualizations. Integrates natively with AnnData and the full scverse stack.

Novae is a graph-based foundation model for spatial transcriptomics data, published in Nature Methods (2025) and integrated into the scverse ecosystem. It is a self-supervised graph attention network enabling zero-shot or fine-tuned spatial domain identification, native batch-effect correction across technologies, and spatially variable gene and pathway analysis. Trained on ~30 million cells across 18 tissues from Xenium, MERSCOPE, and CosMX platforms.

Nicheformer is a transformer-based foundation model published in Nature Methods (2025, vol. 22, pp. 2525–2538), pretrained on SpatialCorpus-110M — a curated corpus of over 57 million dissociated and 53 million spatially resolved cells across 73 tissues from human and mouse. The model enables prediction of spatial context for dissociated scRNA-seq cells, spatial composition prediction, and label transfer via linear probing and fine-tuning. Key finding: models trained only on dissociated data fail to recover spatial microenvironment complexity, underscoring the need for joint single-cell and spatial pretraining.

The twelfth CSHL meeting on CRISPR and genome engineering, covering novel CRISPR technologies, DNA repair, transcriptome engineering, and therapeutic applications. Held August 11–15, 2026 at Cold Spring Harbor, NY. Abstract deadline was June 8, 2026; late registration applies after August 6, 2026.

A joint Keystone Symposium (with Tissue and Spatial Immunology) bridging single-cell genomics, spatial biology, and perturbation technologies with a focus on high-burden diseases and clinical translation. Held February 15–18, 2027 at Fairmont Banff Springs, Banff, Canada. Scholarship and short talk deadline October 21, 2026; early registration December 16, 2026; poster deadline January 25, 2027.